Titlebook: Computer Vision and Image Processing; 7th International Co Deep Gupta,Kishor Bhurchandi,Sanjeev Kumar Conference proceedings 2023 The Edito

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,An Explainable Transfer Learning Based Approach for?Detecting Face Mask,orrectly. The second dataset consists of masked faces and faces without masks. To validate the generalization capability of the proposed model, the trained model is tested on two new standard datasets. In addition to that, the testing is done on a dataset created by ourselves. The proposed model per

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,A Segmentation Based Robust Fractional Variational Model for?Motion Estimation, which is a union of disjoint and independently moving regions such that each motion region contains objects of equal flow velocity. The resulting fractional order partial differential equations are numerically discretized using Grünwald–Letnikov fractional derivative. The nonlinear formulation is t

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,CandidNet: A Novel Framework for?Candid Moments Detection,id). The scoring mechanism allows us to compare images based on their candidness. A detailed ablation study conducted on the proposed framework with various configurations proves the efficacy of the method with a classification accuracy of 92% on CELEBA-HQ [.] and 94% on CANDID-SCORE [.]. With a hig

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,Cost Efficient Defect Detection in?Bangle Industry Using Transfer Learning,-labeled images collected from one of the bangle factories, which act as a seed to train the network which can detect common defects. We present an extensive evaluation of performance of various machine learning algorithms on our dataset using traditional features, and features extracted from popula

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https://doi.org/10.1007/978-3-662-53018-4ge. (2) An extractor that reverse-engineers the embedder function to extract the hidden data inside the encoded image. A multi-discriminator GAN framework with multi-objective training for multimedia hiding is one of the novel contributions of this work.